Abstract:
In one embodiment, a method includes receiving, from a client device of a first user of an online social network, a search query associated with a first topic. The method also includes identifying one or more key-authors associated with the first topic. The method further includes retrieving multiple objects of the online social network matching the search query, where one or more of the retrieved objects are associated with the first topic and are authored by at least one of the identified key-authors. The method also includes generating multiple search-results modules, each search-result module including references to one or more of the retrieved objects. At least one of the search-results modules is a key-authors-module that includes references to one or more of the retrieved objects associated with the first topic that are authored by at least one of the identified key-authors.
Abstract:
In one embodiment, a method includes accessing a set of queries of an online social network received from one or more users of the online social network, parsing each query using a parsing algorithm to generate a query command based on each query, each query command comprising one or more query constraints for a specified number of objects of a specified object-type as specified by parsing-configuration parameters of the parsing algorithm, retrieving the specified number of objects that match at least a portion of the query constraint from one or more data stores associated with the online social network, scoring each retrieved object based on a scoring algorithm, and generating one or more revised parsing-configuration parameters based on a comparison of the scores of the retrieved objects and the specified number of objects of the query constraints.
Abstract:
In one embodiment, a method includes accessing a set of queries of an online social network received from one or more users of the online social network, parsing each query using a parsing algorithm to generate a query command based on each query, each query command comprising one or more query constraints for a specified number of objects of a specified object-type as specified by parsing-configuration parameters of the parsing algorithm, retrieving the specified number of objects that match at least a portion of the query constraint from one or more data stores associated with the online social network, scoring each retrieved object based on a scoring algorithm, and generating one or more revised parsing-configuration parameters based on a comparison of the scores of the retrieved objects and the specified number of objects of the query constraints.
Abstract:
In one embodiment, a method includes identifying a trending topic on an online social network, accessing a plurality of content objects posted to the online social network, wherein each content object is associated with the trending topic, and categorizing each content object into clusters based on a natural-language analysis of the content objects. The method may further include calculating a quality score for each cluster, wherein the quality score for each cluster is based at least on a measure of recency of one or more publication dates of the content objects within the cluster, select the cluster with the highest quality score as a trending cluster, and generating a trending-topic interface that includes a headline and description of the trending topic, wherein the headline and description are extracted from one or more of the content objects within the trending cluster.
Abstract:
In one embodiment, a method includes receiving a query associated with a trending topic selected by a user of an online social network from multiple trending topics and rewriting the query into a query command including multiple query constraints. The method also includes identifying one or more posts matching the query command, where each identified post has privacy settings making the post visible to all users of the online social network, and calculating, for each of the identified posts, a score for the post based on one or more post-quality features, where the score is calculated using a machine-learning model that assigns a particular weight to each of the one or more post-quality features. The method also includes sending to the user a commentary module including at least a portion of each of one or more of the identified posts having scores higher than a threshold score.
Abstract:
In one embodiment, a method includes accessing one or more posts of an online social network; extracting n-grams from each post; determining, for each post, whether it is associated with a trending topic based on whether one or more of the extracted n-grams are associated with the trending topic; caching each post determined to be associated with the trending topic in a corresponding conversation cache; calculating a quality-score for each cached post; and generating a live-conversation module comprising one or more of the cached posts having a quality-score above a threshold quality-score.
Abstract:
In one embodiment, a method includes receiving, from a client device of a first user of an online social network, a search query associated with a first topic. The method also includes identifying one or more key-authors associated with the first topic. The method further includes retrieving multiple objects of the online social network matching the search query, where one or more of the retrieved objects are associated with the first topic and are authored by at least one of the identified key-authors. The method also includes generating multiple search-results modules, each search-result module including references to one or more of the retrieved objects. At least one of the search-results modules is a key-authors-module that includes references to one or more of the retrieved objects associated with the first topic that are authored by at least one of the identified key-authors.
Abstract:
In one embodiment, a method includes receiving a text query from a client system of a user and parsing the text query to identify a primary entity referenced in the text query. The method also includes identifying one or more related entities for the primary entity based on one or more related-entity indexes associated with the primary entity and identifying one or more content objects matching the text query, each identified content object being associated with one or more of the related entities. The method also includes sending to the client system instructions for presenting one or more search results corresponding to one or more of the identified content objects, respectively, each search result including a reference to the associated related entity and a snippet for the related entity describing the relationship between the primary entity and the related entity.
Abstract:
In one embodiment, a method includes receiving a query to search for posts of the online social network; searching an index to identify one or more posts of the online social network that match the query, each post linking to an external object hosted by a third-party system, wherein the index includes a counter that records a number of social signals associated with each external object within the online social network; scoring each of the identified posts based at least in part on the counter associated with the external object linked to the post; and sending, to the client system of the first user, a search-results page including one or more search results, each search result including a reference to an identified post having a score greater than a threshold score.
Abstract:
In one embodiment, a method includes accessing a data set including a list of objects matching a query command and a score for each of the listed objects, where the query command is generated by parsing a query using a parsing algorithm, and where the score for each of the listed objects is calculated based on a scoring algorithm. The method also includes generating multiple subsets of the data set, each subset including one or more of the listed objects, and calculating, for each subset, a measure of score-quality associated with the scores of the objects in the subset and a measure of CPU-power associated with an amount of processing power required for retrieving the objects in the subset. The method also includes revising the parsing algorithm based on a comparison of the measures of score-quality and the measures of CPU-power associated with one or more of the subsets.